scholarly journals An in silico approach to analyze HCV genotype-specific binding-site variation and its effect on drug–protein interaction

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Ramsha Khalid ◽  
Muhammad Faraz Anwar ◽  
Muhammad Aanish Raees ◽  
Sadaf Naeem ◽  
Syed Hani Abidi ◽  
...  
Keyword(s):  
Amino Acid ◽  
Protein Interaction ◽  
Protein Interactions ◽  
In Silico ◽  
Specific Binding ◽  
Antiviral Treatment ◽  
Amino Acid Sequences ◽  
Genotype 1A ◽  
Genotype Variation ◽  
Site Variation

AbstractGenotype variation in viruses can affect the response of antiviral treatment. Several studies have established approaches to determine genotype-specific variations; however, analyses to determine the effect of these variations on drug–protein interactions remain unraveled. We present an in-silico approach to explore genotype-specific variations and their effect on drug–protein interaction. We have used HCV NS3 helicase and fluoroquinolones as a model for drug–protein interaction and have investigated the effect of amino acid variations in HCV NS3 of genotype 1a, 1b, 2b and 3a on NS3-fluoroquinolone interaction. We retrieved 687, 667, 101 and 248 nucleotide sequences of HCV NS3 genotypes 1a, 1b, 2b, and 3a, respectively, and translated these into amino acid sequences and used for genotype variation analysis, and also to construct 3D protein models for 2b and 3a genotypes. For 1a and 1b, crystal structures were used. Drug–protein interactions were determined using molecular docking analyses. Our results revealed that individual genotype-specific HCV NS3 showed substantial sequence heterogeneity that resulted in variations in docking interactions. We believe that our approach can be extrapolated to include other viruses to study the clinical significance of genotype-specific variations in drug–protein interactions.

scholarly journals Prediction of the allergic response of extracellular amylase producing bacteria through in-silico method

2019 ◽  
Vol 10 (2) ◽  
pp. 1185-1189
Author(s):  
Neha Sharma ◽  
Shuchi Kaushik ◽  
Rajesh Singh Tomar
Keyword(s):  
Amino Acid ◽  
In Silico ◽  
Soil Bacteria ◽  
Correct Diagnosis ◽  
Extracellular Enzyme ◽  
Amino Acid Sequences ◽  
Allergic Response ◽  
Alternative Source ◽  
Epitope Region ◽  
Industrial Soil

Allergies intolerance is a common problem worldwide. The major difficulties are related to the correct diagnosis of causes which is associated with amino acid sequences present in the epitope region of allergen. So there is a need to find out the factors causing allergies and allergens themselves. In the present study a bioinformatics tool is used to predict amino acid sequence and mast cell association with different integrated approaches. Internet databases for amylase producing bacteria were used in In-silico method to check the allergy for microorganism producing the extracellular enzyme. Amylase is an extracellular enzyme isolated from soil bacteria Salmonella species and Proteus vulgaris. It is very important in the pharmaceutical industry to check the allergenicity of any drug, protein or enzyme that be used in the treatment of diseases or food industries for various purpose. The aim of the present study is isolation and characterisation of extracellular enzyme produced from soil bacteria and to analyzed allergic response through AlgPred tool of bioinformatics. From results, it was concluded that the protein sequence of amylase did not contain any epitope, no hits for mast and blast which proved that it was not an allergen. So, bacterial isolates from the industrial soil are a good alternative source of enzyme production and may be used as an industrial level. Thus, from the results, it may be concluded that microbes from soil sample can be a good source of industrially important enzymes without any allergy.

scholarly journals In Silico Engineering of Synthetic Binding Proteins from Random Amino Acid Sequences

iScience ◽  
2019 ◽  
Vol 11 ◽  
pp. 375-387 ◽  
Author(s):  
Daniel Burnside ◽  
Andrew Schoenrock ◽  
Houman Moteshareie ◽  
Mohsen Hooshyar ◽  
Prabh Basra ◽  
...  
Keyword(s):  
Amino Acid ◽  
In Silico ◽  
Binding Proteins ◽  
Amino Acid Sequences

scholarly journals In silico prediction of the functional and structural consequences of the non-synonymous single nucleotide polymorphism A122V in bovine CXC chemokine receptor type 1

2020 ◽  
Vol 80 (1) ◽  
pp. 39-46
Author(s):  
A. F. Guzzi ◽  
F. S. L. Oliveira ◽  
M. M. S. Amaro ◽  
P. F. Tavares-Filho ◽  
J. E. Gabriel
Keyword(s):  
Amino Acid ◽  
Chemokine Receptor ◽  
In Silico ◽  
Alpha Helix ◽  
Amino Acid Sequences ◽  
Receptor Type ◽  
Amino Acid Residues ◽  
Causal Polymorphism ◽  
Cxc Chemokine

Abstract The current study aimed to assess whether the A122V causal polymorphism promotes alterations in the functional and structural proprieties of the CXC chemokine receptor type 1 protein (CXCR1) of cattle Bos taurus by in silico analyses. Two amino acid sequences of bovine CXCR1 was selected from database UniProtKB/Swiss-Prot: a) non-polymorphic sequence (A7KWG0) with alanine (A) at position 122, and b) polymorphic sequence harboring the A122V polymorphism, substituting alanine by valine (V) at same position. CXCR1 sequences were submitted as input to different Bioinformatics’ tools to examine the effects of this polymorphism on functional and structural stabilities, to predict eventual alterations in the 3-D structural modeling, and to estimate the quality and accuracy of the predictive models. The A122V polymorphism exerted tolerable and non-deleterious effects on the polymorphic CXCR1, and the predictive structural model for polymorphic CXCR1 revealed an alpha helix spatial structure typical of a receptor transmembrane polypeptide. Although higher variations in the distances between pairs of amino acid residues at target-positions are detected in the polymorphic CXCR1 protein, more than 97% of the amino acid residues in both models were located in favored and allowed conformational regions in Ramachandran plots. Evidences has supported that the A122V polymorphism in the CXCR1 protein is associated with increased clinical mastitis incidence in dairy cows. Thus, the findings described herein prove that the replacement of the alanine by valine amino acids provokes local conformational changes in the A122V-harboring CXCR1 protein, which could directly affect its post-translational folding mechanisms and biological functionality.

In Silico Design of Fusion Toxin DT389GCSF and a Comparative Study

2020 ◽  
Vol 16 (3) ◽  
pp. 238-244 ◽  
Author(s):  
Maryam G. Siahmazgi ◽  
Mohammad A.N. Khalili ◽  
Fathollah Ahmadpour ◽  
Sirus Khodadadi ◽  
Mehdi Zeinoddini
Keyword(s):  
Fusion Protein ◽  
Protein Interactions ◽  
In Silico ◽  
Stimulate Factor ◽  
Web Server ◽  
Colony Stimulate Factor ◽  
Protein Docking ◽  
Amino Acid Sequences ◽  
Fusion Toxin ◽  
Normal Tissues

Background: Chemotherapy and radiotherapy have negative effects on normal tissues and they are very expensive and lengthy treatments. These disadvantages have recently attracted researchers to the new methods that specifically affect cancerous tissues and have lower damage to normal tissues. One of these methods is the use of intelligent recombinant fusion toxin. The fusion toxin DTGCSF, which consists of linked Diphtheria Toxin (DT) and Granulocyte Colony Stimulate Factor (GCSF), was first studied by Chadwick et al. in 1993 where HATPL linker provided the linking sequence between GCSF and the 486 amino acid sequences of DT. Methods: In this study, the fusion toxin DT389GCSF is evaluated for functional structure in silico. With the idea of the commercial fusion toxin of Ontak, the DT in this fusion protein is designed incomplete for 389 amino acids and is linked to the beginning of the GCSF cytokine via the SG4SM linker (DT389GCSF). The affinity of the DT389GCSF as a ligand with GCSF-R as receptor was compared with DT486GCSF as a ligand with GCSF-R as receptor. Both DT486GCSF and its receptor GCSF-R have been modeled by Easy Modeler2 software. Our fusion protein (DT389GCSF) and GCSF-R are modeled through Modeller software; all of the structures were confirmed by server MDWEB and VMD software. Then, the interaction studies between two proteins are done using protein-protein docking (HADDOCK 2.2 web server) for both the fusion protein in this study and DT486GCSF. Results: The HADDOCK results demonstrate that the interaction of DT389GCSF with GCSF-R is very different and has a more powerful interaction than DT486GCSF with GCSF-R. Conclusion: HADDOCK web server is operative tools for evaluation of protein–protein interactions, therefore, in silico study of DT389GCSF will help with studying the function and the structure of these molecules. Moreover, DT389GCSF may have important new therapeutic applications.

In Silico Pharmaco-Gene-Informatic Identification of Insulin-Like Proteins in Plants

2013 ◽  
pp. 948-963 ◽  
Author(s):  
Koona Saradha Jyothi ◽  
G. R. Sridhar ◽  
Kudipudi Srinivas ◽  
B. Subba Rao ◽  
Allam Apparao
Keyword(s):  
Amino Acid ◽  
Human Insulin ◽  
Vigna Unguiculata ◽  
Protein Function ◽  
In Silico ◽  
Cell Envelope ◽  
Amino Acid Sequences ◽  
Jack Bean ◽  
Canavalia Ensiformis ◽  
Bauhinia Purpurea

This chapter presents an extension of the authors’ earlier work, where they showed that nucleotide/amino acid sequences related to insulin occurred in the plant kingdom. It was believed that plants did not have, nor did they need insulin, a protein hormone considered to be restricted to the animal kingdom. In the current study, the human insulin sequence was initially obtained from UniProt/SwissProt (accession no. P01308). Plant genome sequences were obtained from NCBI PubMed (Bauhinia purpurea [Gi|229412], Vigna unguiculata [P83770], and Canavalia ensiformis [Gi|7438602]. Scores were obtained from ProtFun 2.2 [http://www.cbs.dtu.dk/services/ProtFun/]. At the next stage, functions of insulin and glucokinin (insulin like proteins in plants) were predicted by the Protein Function Prediction database (http://dragon.bio.purdue.edu/pfp/index.html), followed by functional site prediction from the ELM database (http://elm.eu.org/). ProtFun predicted the following functions: human insulin (Cell envelope), Jack bean (Energy metabolism), Bauhinia purpurea(Translation). The amino acid Glycine at 32 positions was most highly conserved. Present predictions advocate the use of these sequences (QHLCGS motif) as targets for probing the other plants with lesser homology. In summary our in silico studies have suggested that Bauhinia purpurea (Purple orchid tree-BP), Vigna unguiculata (Cow pea-CP) and Canavalia ensiformis (Jack bean-JB) have conserved the important regions of the human insulin protein.

Abstract 13295: Novel Experimental Therapeutics for COVID-19 Derived From a Nitric Oxide Donor

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
John F Schmedtje ◽  
Zahra Assar
Keyword(s):  
Nitric Oxide ◽  
Protein Interactions ◽  
In Silico ◽  
Vascular Endothelial Cells ◽  
Specific Binding ◽  
Nitric Oxide Donor ◽  
Isosorbide Mononitrate ◽  
Vascular Endothelial ◽  
No Donor ◽  
Glide Docking

Urea transport protein B, the product of the gene SLC14A1 , facilitates transport of urea, water and urea analogues across cell membranes. SLC14A1 mRNA is overexpressed in human vascular endothelial cells in culture under hypoxic (1% oxygen) conditions compared with normoxia. This leads to transport of urea out of the endothelial cell and likely contributes to the reduction in eNOS (endothelial nitric oxide synthase) pathway activity in hypoxia. NO has antiviral activity. Novel compounds were developed by binding a urea-like moiety to the backbone of the generic agent isosorbide mononitrate, a well-known NO donor, to combat vascular endothelial dysfunction in COVID-19, a disease characterized by systemic hypoxia and inflammation due to SARS-CoV-2 infection. A study of drug-protein interactions was undertaken using in silico modelling. Novel compounds were studied against 9 key SARS-CoV-2 targets using Maestro, Schrödinger Suite software (Glide docking). Docking scores and intermolecular interactions within the target’s key binding amino acid residues were studied to compare investigational compounds and known antivirals. Several novel agents tested had a better Glide Score (a prediction of ligand affinity) against the papain-like protease (PL pro ) of SARS-CoV-2 compared with known antiviral drugs. PL pro is considered to be a primary target for therapeutic inhibition of the SARS viruses. The candidate compounds CR-305, CR-607, CR-510 and CR-605 were all superior to Remdesivir, GS-441524, Lopinavir, Boceprevir, and Ribavirin. Given the known direct antiviral action of NO and evidence of specific binding of these compounds to the PL pro of SARS-CoV-2 based on the in silico results, we conclude there is a high likelihood these novel compounds will prove to be of therapeutic value against COVID-19. CR-305 appears to have a higher affinity to SARS-CoV-2 than other antivirals as it sits firmly in the PL pro catalytic pocket and makes the most of key interactions with the catalytic pocket residues: Gly163, Asp164, Gln271 and Tyr264. These data call for a new focus on these novel antiviral agents as they appear to bind with an increased avidity to PL pro (compared with other known antivirals) while targeting delivery of NO to the SARS-CoV-2 virus in COVID-19.

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